Common mental disorder and its association with academic performance among Debre
Berhan University students, Ethiopia
Haile, Yohannes Gebreegziabhere; Alemu, Sisay Mulugeta; Habtewold, Tesfa
Published in:International journal of mental health systems DOI:
10.1186/s13033-017-0142-6
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Publication date: 2017
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Haile, Y. G., Alemu, S. M., & Habtewold, T. (2017). Common mental disorder and its association with academic performance among Debre Berhan University students, Ethiopia. International journal of mental health systems, 11(34). https://doi.org/10.1186/s13033-017-0142-6
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RESEARCH
Common mental disorder and its
association with academic performance
among Debre Berhan University students,
Ethiopia
Yohannes Gebreegziabhere Haile
1*, Sisay Mulugeta Alemu
2and Tesfa Dejenie Habtewold
3Abstract
Background: Common mental disorder (CMD) is prevalent in industrialized and non-industrialized countries. The
prevalence of CMD among university students was 28.8–44.7% and attributed to several risk factors, such as school-ing. The aim of this study was to assess the prevalence and risk factors of CMD. In addition, the association between CMD and academic performance was tested.
Methods: Institution based cross-sectional study was conducted with 422 students at Debre Berhan university from
March to April 2015. CMD was the primary outcome variable whereas academic performance was the secondary outcome variable. Kessler psychological distress (K10) scale was used to assess CMD. Bivariate and multiple logistic regression analysis were performed for modeling the primary outcome variable; independent samples T test and linear regression analysis were carried out for modeling the secondary outcome variable. The strength of association was interpreted using odds ratio and regression coefficient (β) and decision on statistical significance was made at a p value of 0.05. Data were entered using EPI-data version 3.1 software and analyzed using the Statistical Package for the Social Sciences (SPSS) version 20.01 software.
Results: The prevalence of CMD was 63.1%. Field of study (p = 0.008, OR = 0.2, 95% CI 0.04–0.61), worshiping
(p = 0.04, OR = 1.8, 95% CI 1.02–3.35), insomnia (p < 0.001, OR = 3.8, 95% CI 2.21–6.57), alcohol drinking (p = 0.006, OR = 2.7, 95% CI 1.33–5.66), and headache (p = 0.02, OR = 2.1, 95% CI 1.10–3.86) were identified risk factors for CMD. The mean cumulative grade point average of students with CMD was lower by 0.02 compared to those without CMD, but not statistically significant (p = 0.70, β = −0.02, 95% CI −0.15 to 0.10). CMD explained only 0.8% (r2 = 0.008) of the difference in academic performance between students.
Conclusions: At least three out of five students fulfilled CMD diagnostic criteria. The statistically significant risk factors
were field of study, worshiping, insomnia, alcohol drinking, and headache. Moreover, there was no statistically signifi-cant association between CMD and academic performance. Undertaking integrated evidence-based intervention focusing on students with poor sleep quality, poor physical health, and who drink alcohol is essential if the present finding confirmed by a longitudinal study.
Keywords: Common mental disorder, Prevalence, Academic performance, Students, Ethiopia
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Open Access
*Correspondence: yohannes36@gmail.com
1 Department of Nursing, College of Health Science, Debre Berhan University, 445, Debre Berhan, Ethiopia
Background
Mental health is a state of well-being in which every indi-vidual realizes his or her own potential, can cope with the normal stresses of life, can work productively and fruitfully, and able to contribute to her or his commu-nity [1]. Mental disorder is a syndrome characterized by a clinically significant disturbances in cognition, emotion regulation, or behavior accompanied by psychological, biological, or developmental processes dysfunction [2]. Mental disorders account for 14% of the global burden of disease; 75% of affected people are living in low-income countries [3]. In Ethiopia, mental disorder is the leading non-communicable disorder which made up 11% of the total burden of disease [4].
The social environment, academic norms, and psycho-somatic reactions to diverse situation potentially affect the mental health of university students [5]. Research conducted by the National Alliance on Mental Illness in the US have shown that 25% college students had a diagnosable illness, 40% did not seek help, 80% felt over-whelmed by their responsibilities, and 50% had anxiety [6]. The American College Health Association survey report in 2010 also revealed that 45.6% of the students feeling hopeless and 30.7% feeling depressed [7].
The prevalence of mental distress, a non-specific form of altered mental health, in Ethiopian university students was found to be 21.6–49.1% [8–11]. The most consist-ent associated factors were a family history of mental illness, frequent conflicts with fellows, Khat chewing, worshiping, batch of students, field of study, level of training, and age [8–11]. In addition, another study reported that mental distress has been associated with the difficulty in making friends and dating, active sexual practice, income and stationary materials inadequacy, lack of adequate access to academic reference materials, lack of adequate access to sanitary and recreational facil-ity, overcrowding, and worrying about personal safety [11].
Common mental disorder (CMD), also known as a minor psychiatric disorder, is characterized by insom-nia, fatigue, irritability, forgetfulness, difficulty in con-centration, and somatic complaints [12]. Globally, the prevalence of CMD was ranging from 7 to 50% [13–22]. Similarly, a meta-analysis of 174 studies concluded that the 1-year prevalence of CMD was 17.6% and the life-time prevalence was 29.2%; both estimates were low in Asia and Sub-Saharan African countries [23]. Moreover, a cross-sectional survey in England, Wales and Scotland revealed that the prevalence of CMD was 17–31% [24,
25].
The prevalence of CMD was 28.8–44.7% among uni-versity students [26–30], 43.3% among community-based
health agents [31], 50.1% among socio-educational agents [32], 22–42.6% among primary healthcare workers [33, 34], 22.3–34.5% among university employees [35], 30.2–50% among patients [36–39], 41.4% among preg-nant women [40], 29.7–32.1% among elders [41, 42], 24% among physicians [43], and 6.7% among civil aviation pilots [44].
CMD has been associated with several factors. A sys-tematic review of 115 studies in low and middle-income countries reported that CMD was strongly associated with poverty, education, food insecurity, housing, social class, socio-economic status, and financial stress [45]. Similarly, cross-sectional studies conducted in South America identified poverty, schooling, social inequal-ity, low income, sex, age, employment status, inadequate body weight perception, tobacco smoking, violence, poor social support, sedentary behavior and body image dis-satisfaction were risk factors of CMD [16, 17, 19, 20, 35,
36, 46, 47]. Moreover, Harpham et al. [18] found out gen-der, educational status, and violence were the risk factors of CMD. Weich et al. [24, 25] also concluded that high-income individuals to be more prone to CMD and vice versa.
Even though CMD is common in the general popula-tion, young people particularly university students are more susceptible [18, 46, 48]. A cross-sectional study with university students uncovered that the prevalence of CMD was 28.8–44.7% [26–30]. The risk factors were diffi-culty in making friends, poor self-evaluation of academic performance, thoughts of dropping out, sleep disorder, not owning a car, feeling overloaded, discrimination, limited physical activity, and perceived lack of emotional support [26–30]. A large cross-sectional web-based study conducted at the University of Newcastle found that nearly one-third of students reported at least one CMD [49]. The risk factors were financial stress, living alone, and low socioeconomic background [50, 51]. In addition, the prevalence of CMD among Dutch university medical students was 48–54% [52]. Another cross-sectional study conducted at the public university in Northeast Brazil reported that the prevalence of CMD was 33.7%; the risk factors were gender, lack of good expectations regarding the future, course as not a source of pleasure, and feeling emotionally tense [53].
The high public health burden of CMD has an impact on students interpersonal relationships and quality of life perhaps that affects their academic performance [27]. In addition, comparative data from the US have shown a sig-nificant link between high levels of psychological distress and low academic performance among college students [54]. Moreover, another earlier study discovered the asso-ciation of mental illness and termination of university
education, difficulty with time and resource manage-ment, and a decreased likelihood to seek academic assis-tance [55]. However, little is known about CMD in Sub-Saharan African countries particularly in Ethiopia. This gap pointed out the need to conduct further stud-ies to measure the magnitude of mental health problem among university students and initiate culturally tailored evidence-based interventions [56]. Thus, the aim of this study was to assess the prevalence and risk factors of CMD. In addition, the association between CMD and academic performance was tested.
Methods
Study setting, design, and procedure
Institution based cross-sectional study was conducted at Debre Berhan University from March to April 2015. Debre Berhan University is located 130 km northeast from Addis Ababa, the capital city of Ethiopia. Cur-rently, more than 14,000 regular, weekend, and summer program students were enrolled in 35 departments [57]. Undergraduate students who were enrolled in 2014/2015 full-time study, capable of independent communication, and provided informed written consent were included. All students were selected by proportionate stratified random sampling method. First, stratum was created using each discipline/college as a cluster. Second, stu-dents list was obtained from the academic record office. Third, based on the calculated sample size, the required number of students were allocated to each college pro-portional to the total number of students enrolled in the corresponding college. Fourth, simple random sampling method was used to reach the individual student. The sample size was determined using single population pro-portion formula considering the following assumptions: the prevalence of CMD was 50%, the margin of error was 5%, and confidence level was 95%. After adjustment for 10% non-response rate, the final sample size was 422.
Variables
Common mental disorder (CMD) was the primary out-come variable. CMD was diagnosed if Kessler psycho-logical distress (K10) scale score was ≥7. Academic performance was the secondary outcome variable. Self-reported cumulative grade point average (CGPA) was used as a proxy measure of academic performance. Socio-demographic characteristics, substance use habit, and physical illness symptoms were the explanatory vari-ables. Insomnia was assessed using the Pittsburgh Sleep Quality Index (PSQI) standard instrument with a global score cut-off value of >5 for cases. Worshipping was defined as any reported religious practice performed by students irrespective of their religion.
Data collection and instrument
The data were collected from nine disciplines using a structured self-administered questionnaire. The ques-tionnaire had four different sub-sections: section one-sociodemographic characteristics; section two-K10 scale; section three-substance use habit; and section four-physical and psychological symptoms. K10 scale is a 10-item questionnaire that a person rating the 30 days anxiety and depressive symptoms experience in a five-level Likert scale. K10 scale has already been validated in Ethiopia by Tesfaye et al. [58] and yielded an excel-lent internal consistency of 0.93, sensitivity of 84.2%, and specificity of 77.8% at a cut-off point of 6/7. Thus, it was reasonable to use for this study population. The data were collected by 35 trained university instruc-tors. Supervisors provided all relevant support when necessary.
Instrument reliability analysis
The K10 scale items had an excellent reliability for this study population. The interclass correlation (Cronbach’s Alpha) of items was 0.900 with Cronbach’s Alpha based on standardized items value of 0.901. Two-way mixed effects model and average consistency measure were used to measure the intraclass correlation of items, which was 0.9 (95% CI 0.88, 0.91).
Data processing and analysis
Before analysis, the data passed through stringent qual-ity control process and inconsistencies, outliers, and missing values were checked using frequency distribu-tion. Multiple imputations (5×) was done assuming the data values were missing at random. First, all explana-tory variables were fitted step-by-step to the bivariate logistic regression model. Then, multiple logistic regres-sion model analysis was done. Finally, the independent risk factors were selected if the p value was ≤0.05. The strength of association was determined using odds ratios with 95% confidence interval. Independent Samples T test was used to test the group difference in academic performance related to CMD while linear regression analysis was done to investigate the association between CMD and academic performance and estimate the explained variance. The effect of CMD on academic per-formance was interpreted using regression coefficient (β). Finally, the results were presented using charts and tables. EPI-data version 3.1 software was used for data entry, variable coding, and cleaning while SPSS ver-sion 20.01 software was used for analysis. The study was adherent to the Strengthening the Reporting of Obser-vational Studies in Epidemiology (STROBE) statement [59].
Results Missing data
In this study, even if some data were missing for the independent variables, no data was missing for depend-ent variables (K10 scale). Analysis of patterns of missing values revealed that a total of 28 variables had at least one missing value and a total of 249 students didn’t reply at least for one variable. Overall, 4% of the total sample data was missing. Since only a small percentage of the data was missing and the sample size was small, multiple imputation was done to handle missingness.
Socio‑demographic characteristics
Of the 422 students invited, 388 (91.9%) completed the self-administered questionnaire and 78.4% (304/388) were male. The mean age of students was 22.13 year (SD = 2.12). As illustrated in Table 1, 29.6% (115/388) of students were fifth year, 72.4% (281/388) were Amhara, 76.5% (297/388) were single, and 85.1% (330/388) were Orthodox Christian.
Substance use habit
As shown below in Table 2, 95.4% (370/388) of students did not smoke cigarettes, 92.3% (358/388) did not chew Khat, and 25.8% (100/388) drank alcohol less than once per month.
Physical and psychological complaints
During the last month, 38.9% (151/388) of students had a headache and 36.3% (138/388) had a fever. In addition, 61.6% (239/388) of students were insomniacs (Table 3). Table 1 Socio-demographic characteristics of Debre
Ber-han University students, April 2015
N = 388
a Law, Health Science and Medicine
b Tigray, Gurage, Agaw, Sidama, Afar, Awi, Wolayita, Gamo, Silte, Hadiya, Konso and Gedeo
c Catholic, Adventist and Apostolic church d Divorce and married
e Wood work, university police, daily laborer, helping family, pool keeping, guider, driver, farming, religious education, construction forman, any kind of work, merchant and teacher
Characteristics Frequency K10 score n % Mean SD
Sex
Male 304 78.4 10.45 7.94
Female 84 21.6 10.59 8.88
Field of study
Natural and computational science 51 13.1 11.45 8.63
Agricultural science 24 6.2 9.75 8.00
Business and economics 59 15.2 11.9 7.47
Computer science and IT 25 6.4 12.76 10.11
Engineering 171 44.1 9.48 7.57
Humanity and social science 36 9.3 11.38 9.19
Othersa 22 5.7 8.91 8.54 Educational level 1st year 89 22.9 11.17 8.65 2nd year 100 25.8 10.01 7.98 3rd year 70 18.0 11.16 8.42 4th year 14 3.6 10.50 7.08 5th year 115 29.6 9.90 7.90 Ethnicity Amhara 281 72.4 11.00 8.50 Oromo 47 12.1 8.91 6.81 Othersb 60 15.5 9.24 7.12 Religion Orthodox Christian 330 85.1 10.73 8.28 Protestant 31 8.0 10.16 8.69 Othersc 27 7.0 7.69 4.93 Worshiping Frequently (daily) 171 44.1 9.86 8.52 Less frequently 197 50.8 11.17 7.91 Never 20 5.2 8.95 6.62 Marital status Single 297 76.5 10.48 7.97 In relationship 65 16.8 11.35 8.94 Othersd 26 6.7 8.24 7.99 Additional work Yese 30 7.7 11.66 8.39 No 358 92.3 10.38 8.13
Table 2 Substance use habit of Debre Berhan University students, April 2015
N = 388
Characteristics Frequency K10 score n % Mean SD
Smoking cigarettes
No 370 95.4 10.42 8.02
Yes (any frequency) 18 4.6 11.62 10.62
Chewing Khat
No 358 92.3 10.56 8.15
Yes (any frequency) 30 7.7 9.44 8.14
Drinking alcohol
Never 222 57.2 9.55 8.23
Less than once per month 100 25.8 11.65 7.60
Kessler psychological distress (K10) score and prevalence of common mental disorder (CMD)
The mean of K10 scale score was 10.48 (SD = 8.14) with the maximum score of 39. The prevalence of CMD was 63.1% (245/388). In addition, Fig. 1 gives a graphical description of the relationship between CMD, headache, and insomnia.
Risk factors of CMD
As presented in Table 4, field of study and worshipping were independent socio-demographic risk factors for CMD. Law and Health Science and Medicine students were significantly less likely (80%) develop CMD com-pared to Natural and Computational Science students (p = 0.008, OR = 0.2, 95% CI 0.04–0.61). Students who worshiped less frequently were 1.8 times more likely develop CMD compared to those students who wor-shiped daily (p = 0.04, OR = 1.8, 95% CI 1.02–3.35).
Furthermore, insomnia, alcohol drinking, and head-ache were strongly associated risk factors of CMD. Insomniac students were 3.8 times more likely develop CMD compared to non-insomniacs (p < 0.001, OR = 3.8, 95% CI 2.21–6.57). Students who drink alcohol less than once per month were 2.7 times more likely develop CMD
compared to students never drink alcohol (p = 0.006, OR = 2.7, 95% CI 1.33–5.66). Moreover, students who had headache were 2.1 times more likely develop CMD compared to those who had no headache (Table 5). CMD and academic performance
The mean CGPA was 3.11 (SD = 0.42) with a maximum of 4.00 and a minimum of 1.73 points. Since the distribu-tion of CGPA was normal and all assumpdistribu-tions of linear regression were fulfilled, linear regression analysis was used to test the association between CMD and academic performance. CMD explained only 0.8% (r2 = 0.008) of
CGPA variability between students. The mean CGPA of students with CMD was lower by 0.02 compared to those without CMD. However, it was not significant (p = 0.70, β = −0.02, 95% CI = −0.15–0.10).
Discussion
In this study, the prevalence of CMD was 63.1%. This finding was in line with the previous study report in the Netherland university students [52]. On the other hand, it was approximately two to three times the prevalence of CMD in Ethiopian university students [60], Chilean uni-versity students [61], and Peruvian college students [62]. Moreover, the current study finding was higher than the study report by Silva et al. [63], Volcan et al. [64], and Haregu et al. [65].
In the present study, field of study was one of the risk factors for CMD; Law and Health Science and Medicine students had less odds of CMD compared to Natural and Computational Science students. The possible explana-tion was that Natural and Computaexplana-tional Science stu-dents study a hard science, such as mathematics, physics which is usually stressful and academically demanding to students. In the contrary, recent studies with univer-sity students concluded that the risk of CMD was high among Health Science and Medicine students [26–29]. The present study also uncovered that CMD was signifi-cantly associated with worshipping; students who wor-shiped less frequently were 1.8 times more likely develop CMD compared to those students who worshiped daily. The possible explanation was that worshipping helps to relieve stress and become optimistic about any negative life circumstances. This finding was in congruence with the study report in Brazil college students where low and moderate spiritual wellbeing showed a doubled risk of CMD [64].
Another important significantly associated risk factor was insomnia; insomniac students were 3.8 times more likely develop CMD compared to non-insomniacs. This finding was consistent with other previous studies report by Hidalgo et al. [66] among Brazilian medical students, Byrd et al. [60] among Ethiopian undergraduate students, Table 3 Physical and psychological complaints of Debre
Berhan University students, April 2015
N = 388
a Pain, respiratory disease, gastrointestinal disease, renal disease, and other (anemia, hypertension, fungal infection of the hair, heart problem, ear problem, sadness, hopelessness, fatigue, lack of interest, stress, anxiousness, happiness, and depression)
Characteristics Frequency K10 score
n % Mean SD Headache Yes 151 38.9 13.50 7.91 No 237 61.1 8.53 7.69 Back pain Yes 72 18.6 14.94 8.55 No 316 81.4 9.42 7.68 Fever Yes 138 36.3 12.94 7.95 No 240 63.7 9.04 7.91 Other complaintsa Yes 78 20.1 14.28 7.61 No 310 79.9 9.51 8.01 Suicidal thought Yes 22 5.7 16.54 9.51 No 366 94.3 10.11 7.91 Insomnia No 149 38.4 6.70 5.96 Yes 239 61.6 12.83 8.44
Concepcion et al. [61] among Chilean university stu-dents, Rose et al. [62] among Peruvian college students, and Haregu et al. [65] among Thai college students. Fur-thermore, this study showed that alcohol drinking sig-nificantly increased the risk of CMD; students who drink alcohol less than once per month were 2.7 times more likely develop CMD compared to students never drink alcohol. This finding was similar to the study report by Byrd et al. [60] among Ethiopian undergraduate students, but on the other hand, the study conducted among Chil-ean [61], Peruvian [62], and Thai [65] university students did not confirm this significant association.
Finally, the current study sought the association between CMD and academic performance; the mean CGPA of students with CMD was lower by 0.02 com-pared to those without CMD though insignificant. This does not imply CMD has no relevant effect on students’ academic performance. Therefore, this non-significant result might be due to two reasons. Primarily, this study had used CGPA which might be distorted by previous semester or year grade. This justification was supported by the finding that more than 75% of the students in this study were the second year and above. Secondly, the
data was collected from students who actively attending their education perhaps their coping mechanism is good and academically competent. Nevertheless, the previous studies reported that CMD determine academic perfor-mance [67, 68].
Generally, heterogeneities have seen on the prevalence and risk factors of CMD and the association between CMD and academic performance as well. This might be due to the following reasons. First, Kessler psychological distress (K10) scale was used in the present study whereas all previously reviewed studies were used General Health Questionnaire (GHQ-12) and Self-Report Questionnaire (SRQ-20) to assess mental health status. Second, the cur-rent data was collected during examination week perhaps anticipated stress increased K10 scale score. Third, most of the previous studies were conducted only with medi-cal students; however, this study recruited students from nine disciplines. Fourth, the current study assessed only the 30 days mental health status.
In one hand, by 2030 World Health Organization (WHO) targeted to reduce non-communicable diseases related premature mortality by one-third through pre-vention, treatment, and promotion of mental health [69].
On the other hand, contemporary epidemiological stud-ies in high and low-income countrstud-ies found a significant association between mental disorders and educational
achievement during tertiary education [67, 68]. There-fore, developing (inter)national mental health strat-egy has a pivotal role to achieve WHO health goal and Table 4 Association between CMD and socio-demographic characteristics, April 2015
a Law, Health Science and Medicine
b Tigray, Gurage, Agaw, Sidama, Afar, Awi, Wolayita, Gamo, Silte, Hadiya, Konso and Gedeo c Catholic, Adventist and Apostolic church
d Divorce and married
e Wood work, university police, daily laborer, helping family, pool keeping, guider, driver, farming, religious education, construction forman, any kind of work, merchant and teacher
Variables CMD (K10 score ≥7) Bivariate regression model Multiple regression model No
n (%) Yesn (%) p value OR (95% CI) p value OR (95% CI)
Sex
Male 110 (36.2) 194 (63.8)
Female 33 (39.3) 51 (60.7) 0.63 0.9 (0.54, 1.45) 0.47 1.3 (0.64, 2.58)
Field of study
Natural and computational science 14 (27.5) 37 (72.5)
Agricultural science 7 (29.2) 17 (70.8) 0.88 1.0 (0.31, 2.69) 0.34 0.5 (0.14, 1.97)
Business and economics 16 (27.1) 43 (72.9) 0.97 1.0 (0.44, 2.36) 0.15 0.5 (0.17, 1.33)
Computer science and IT 8 (32.0) 17 (68.0) 0.68 0.8 (0.28, 2.28) 0.13 0.4 (0.09, 1.37)
Engineering 73 (42.7) 98 (57.3) 0.05 0.5 (0.26, 1.01) 0.05 0.4 (0.12, 0.99)
Humanity and social science 13 (36.1) 23 (63.9) 0.39 0.7 (0.27, 1.67) 0.07 0.4 (0.11, 1.07)
Othersa 12 (54.5) 10 (45.5) 0.03 0.3 (0.11, 0.89) 0.01 0.2 (0.04, 0.61) Batch 1st year 27 (30.3) 62 (69.7) 0.12 1.6 (0.88, 2.85) 0.57 0.7 (0.22, 2.35) 2nd year 41 (41.0) 59 (59.0) 0.98 1.0 (0.58, 1.72) 0.27 0.6 (0.23, 1.50) 3rd year 24 (34.3) 46 (65.7) 0.37 1.3 (0.71, 2.46) 0.67 0.8 (0.27, 2.32) 4th year 4 (28.6) 10 (71.4) 0.39 1.7 (0.51, 5.84) 0.72 1.4 (0.24, 8.01) 5th year 47 (40.9) 68 (59.1) Ethnicity Amhara 95 (33.8) 186 (66.2) Oromo 23 (48.9) 24 (51.1) 0.05 0.5 (0.29, 1.01) 0.08 0.5 (0.22, 1.09) Othersb 25 (41.7) 35 (58.3) 0.32 0.7 (0.42, 1.33) 0.30 0.6 (0.29, 1.47) Religion Orthodox Christian 118 (35.8) 212 (64.2) Protestant 15 (48.4) 16 (51.6) 0.14 0.6 (0.27, 1.20) 0.83 0.9 (0.31, 2.56) Othersc 10 (37.0) 17 (63.0) 0.86 0.9 (0.40, 2.14) 0.10 2.6 (0.82, 8.54) Worshiping Frequently (daily) 73 (42.7) 98 (57.3) Less frequently 63 (32.0) 134 (68.0) 0.04 1.5 (1.02, 2.39) 0.04 1.8 (1.02, 3.35) Never 7 (35.0) 13 (65.0) 0.52 1.4 (0.52, 3.60) 0.91 0.9 (0.28, 3.13) Marital status Single 108 (36.4) 189 (63.6) In relationship 22 (33.8) 43 (66.2) 0.49 1.2 (0.68, 2.21) 0.84 1.1 (0.50, 2.31) Othersd 13 (50.0) 13 (50.0) 0.17 0.6 (0.25, 1.27) 0.31 1.8 (0.58, 5.35) Additional work Yese 9 (30.0) 21 (70.0) 0.37 1.5 (0.64, 3.38) 0.48 1.5 (0.50, 4.30) No 134 (37.4) 224 (62.6) Age 0.10 1.0 (0.81, 1.02) 0.16 0.9 (0.72, 1.06)
improve students’ academic accomplishment. For the successful realization of the strategy, academic institu-tions and researchers should provide updated evidence-based information for delivering the most cost effective culturally tailored care.
This study has several implications to develop a univer-sal culturally appropriate screening tool for the students who are at risk of CMD, serve as a baseline for future studies, and provide important evidence to plan need-based interventions for students with CMD. Meanwhile, the universal screening activity is not time-consuming, as a result, it can be integrated into a student clinic at the university. Furthermore, this study will be used as a base-line evidence for future mental heal care planning and intervention.
K10 scale, a standardized validated tool, was used to assess CMD. To the best of our knowledge, this study was the first that assessed CMD using K10 scale in uni-versity students. Moreover, a large number of students were recruited from nine disciplines. However, this study had several limitations. First, self-administered data were used that might added recall bias and socially desirabil-ity bias. Second, the cross-sectional nature of the study does not allow attribution of causality. Hence, the preva-lence of CMD that was reported may not be exclusive to the situation on university alone. Finally, since our study was conducted only in one institution it might limit the external validity of results. However, this limitation was perhaps compensated by the inclusion of students from different ethnicity and socioeconomic group.
Table 5 Association between CMD and substance use habit and health complaints, April 2015
a Pain, respiratory disease, gastrointestinal disease, renal disease, and other (anemia, hypertension, fungal infection of the hair, heart problem, ear problem, sadness, hopelessness, fatigue, lack of interest, stress, anxiousness, happiness, and depression)
Variables CMD (K10 score ≥7) Bivariate regression model Multiple regression model No
n (%) Yesn (%) p value OR (95% CI) p value OR (95% CI)
Cigarettes smoking
No 136 (36.8) 234 (63.2)
Yes (with any frequency) 7 (38.9) 11 (61.1) 0.83 0.9 (0.34, 2.38) 0.95 1.1 (0.23, 4.85)
Khat chewing
No 130 (36.3) 228 (63.7)
Yes (with any frequency) 13 (43.3) 17 (56.7) 0.42 0.7 (0.33, 1.58) 0.39 0.6 (0.15, 2.12)
Alcohol drinking
Never 98 (44.1) 124 (55.9)
Less than once per month 24 (24.0) 76 (76.0) 0.001 2.5 (1.49, 4.35) 0.01 2.7 (1.33, 5.66)
More than once per month 21 (31.8) 45 (68.2) 0.05 1.8 (0.99, 3.23) 0.04 2.4 (1.02, 5.86)
Headache Yes 27 (17.9) 124 (82.1) <0.001 4.4 (2.70, 7.23) 0.02 2.1 (1.10, 3.86) No 116 (48.9) 121 (51.1) Back pain Yes 11 (15.3) 61 (84.7) <0.001 3.6 (1.85, 7.15) 0.05 2.3 (1.00, 5.19) No 132 (41.8) 184 (58.2) Fever Yes 29 (20.6) 112 (79.4) <0.001 3.2 (1.96, 5.11) 0.08 1.7 (0.92, 3.14) No 114 (46.2) 133 (53.8) Other complaintsa Yes 9 (11.5) 69 (88.5) <0.001 5.5 (2.65, 11.24) 0.002 3.9 (1.67, 9.07) No 134 (43.2) 176 (56.8) Suicidal thought Yes 4 (18.2) 18 (81.8) 0.07 2.8 (0.92, 8.41) 0.35 0.5 (0.13, 2.06) No 139 (38.0) 227 (62.0) Insomnia No 86 (57.7) 63 (42.3) Yes 57 (23.8) 182 (76.2) <0.001 4.4 (2.81, 6.77) <0.001 3.8 (2.21, 6.57)
Conclusions
At least three out of five students fulfilled CMD diag-nostic criteria. The statistically significant risk fac-tors were field of study, worshiping, insomnia, alcohol drinking, and headache. Moreover, this study concluded that there was no statistically significant association between CMD and academic performance. Undertak-ing integrated evidence-based intervention focusUndertak-ing on students with poor sleep quality, poor physical health, and who drank alcohol is essential if the present find-ing confirmed by a longitudinal study. The high preva-lence of CMD suggests that immediate preventive and curative measures should be implemented, such as the setting up of psycho-pedagogic support and coun-seling services to build students resilience [53]. Life skill training is also required to openly discuss and actively address the problems during university education [55]. Furthermore, the students should be taught different stress management techniques to improve their abil-ity to cope with a demanding professional course, such as hard science courses [70]. In order to have a better understanding of students’ mental health trajectory and educational achievement, longitudinal and interven-tional study should be conducted.
Authors’ contributions
YG conceived and designed the study. YG and TD analyzed and interpreted the data. YG, SM, and TD wrote the article. All authors read and approved the final manuscript.
Author details
1 Department of Nursing, College of Health Science, Debre Berhan University, 445, Debre Berhan, Ethiopia. 2 Mental Health and Psychosocial Support Pro-gram, International Medical Corps, Dolo Ado, Ethiopia. 3 Department of Epi-demiology and Rob Giel Research Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
Acknowledgements
First of all, our in-depth gratitude goes to Debre Berhan University for the approval of the study and financial support too. Data collectors and respond-ents were highly acknowledged for investing their precious time for collecting data and providing the necessary information.
Competing interests
The authors declare that they have no competing interests.
Availability of data and materials
All the data were included in the article.
Ethics approval and consent to participate
In order to conform the Declaration of Helsinki (1964) and Population Screen-ing Act (WBO), ethical approval was obtained from the ethical review board of Debre Berhan University Institute of Health Science and Medicine. Written informed consent was obtained from each individual participant. Besides, strict confidentiality was ensured using the code for all students and securing all data. The data was and will be used only for research purpose.
Funding
This study was funded by Debre Berhan University. The university has no role in designing, analysis, and writing of the study.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in pub-lished maps and institutional affiliations.
Received: 5 November 2016 Accepted: 21 April 2017
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